Historical Diversity Index for 2000, 2010, and 2020

The histograms show how the amount of diversity in Chicago has increased over time.

Historical Diversity Index Maps for 2000, 2010, and 2020

The maps between the years look very similar, but there are some area that have changed.

## Chicago's ratio of height to width
# bbox(chi_city_outline)["y",] %>% diff %>% unname/
#     bbox(chi_city_outline)["x",] %>% diff %>% unname
# About .91



r <- shp2raster(shp_tracts_2020, column="tot_dens",
                ncells=1000)
plot(r)

r00 <- shp2raster(shp_tracts_2000, column="tot_dens",
                ncells=1000)
plot(r)
plot(r00)
plot(r-r00)


# summary(shp_tracts_2000)
# 
# r00 <- raster(shp_tracts_2000)
# summary(r00)

str(shp_tracts_2020@data)


# r <- rasterize(shp_tracts_2020, 
#                raster(ncol=700, nrow=700),
#                ext=extent(shp_tracts_2020),
#                "tot_pct")
# shp_tracts_2020$ALAND20 %>% sort %>% head
# shp_tracts_2020$tot_dens %>% sort %>% tail
# shp_tracts_2020@data[which(shp_tracts_2020$ALAND20==0),]
# which(shp_tracts_2020$tot_dens==max(shp_tracts_2020$tot_dens, na.rm=T)) %>% shp_tracts_2020@data[.,]
# 
# library(raster)
# x <- shapefile('file.shp')
# crs(x)
# plot(area(shp_tracts_2020) %>% pmin(., 1e8) , shp_tracts_2020$ALAND20)
# hist(area(shp_tracts_2020) %>% .[.<3e7] )
# area(shp_tracts_2020) %>% sort %>% head
# 
# plot(r)
# 
# 
# 
# r <- raster(ncol=700, nrow=700)
# extent(r) <- extent(shp_tracts_2020)
# shp_tracts_2020$temp <- shp_tracts_2020$TOT / as.numeric(shp_tracts_2020$ALAND20)
# rp <- rasterize(shp_tracts_2020, r, 'temp')
# plot(rp)
# 

# # ??raster
# ??bkde2D
# kde <- bkde2D(dat[ , list(longitude, latitude)],
#               bandwidth=c(.0045, .0068), gridsize = c(100,100))
# # Create Raster from Kernel Density output
# KernelDensityRaster <- raster(list(x=kde$x1 ,y=kde$x2 ,z = kde$fhat))
# 
# #create pal function for coloring the raster
# palRaster <- colorNumeric("Spectral", domain = KernelDensityRaster@data@values)
# 
# ## Leaflet map with raster
# leaflet() %>% addTiles() %>% 
#     addRasterImage(KernelDensityRaster, 
#                    colors = palRaster, 
#                    opacity = .8) %>%
#     addLegend(pal = palRaster, 
#               values = KernelDensityRaster@data@values, 
#               title = "Kernel Density of Points")